
Extracted from the Latvian report: Together, these form the SEGN standardised data product that is transferable, auditable and scalable.
The lossless knowledge graph constructed directly from the annual report of the Latvian State Security Bureau (SAB) derives its core value from structural fidelity and traceability to the original text: it faithfully replicates the report's content through multi-level nodes encompassing chapters, paragraphs, and sentences, ensuring any analysis can be precisely traced back to its source location. This resolves the question of whether the text has been faithfully preserved. However, such lossless graphs remain fundamentally confined to the textual structural mapping layer. They do not automatically address analytical questions such as: how the report semantically organises threat perceptions, through which mechanisms judgements are formed, and whether these judgements possess sufficient evidentiary grounding. By contrast, the SEGN standardised digital product, built upon this lossless graph, introduces computable reasoning layers and audit interfaces. It explicitly models concepts, mechanisms, and causal relationships within the text, mandating that each inference aligns with evidence at the page-level. This elevates national security reports from ‘readable text’ to ‘computable, auditable, and transferable semantic systems’. Within this framework, strategic assessments in reports are reconfigured from narrative conclusions into interrogable chains of reasoning that can be verified and cross-referenced. This establishes a replicable research paradigm for semantic analysis of intelligence texts across nations and years. This represents SEGN's fundamental advancement beyond conventional lossless knowledge graphs.

从拉脱维亚报告提取的：三者一起就是 可迁移、可审计、可扩展 的 SEGN 标准化数据产品。
直接从拉脱维亚国家安全局（SAB）年度报告构建的无损知识图谱，其核心价值在于对原始文本的结构性保真与可追溯性：它以章节、段落、句子等多级节点完整复刻报告内容，确保任何分析均可精确回溯至原文位置，从而解决“文本是否被忠实保留”的问题。然而，这种无损图谱本质上仍停留在文本结构映射层，并不自动回答报告“在语义上如何组织威胁认知、通过何种机制形成判断、以及这些判断是否具备证据充分性”等分析性问题。相比之下，基于该无损图谱进一步构建的 SEGN 标准化数字产品，通过引入可计算推理层与审计接口，将文本中的概念、机制与因果关系显式建模，并强制每一项推理结果与页码级证据对齐，使国家安全报告从“可阅读文本”升级为“可计算、可审计、可迁移的语义系统”。在这一框架下，报告中的战略判断不再只是叙述性结论，而是被重构为可被质疑、复核与比较的推理链条，从而为跨国家、跨年度的情报文本语义分析提供了可复制的研究范式。这正是 SEGN 相对于单纯无损知识图谱的根本跃迁所在。